22 papers · ranked by Valyu relevance
Xi Chen, Yateng Tang, Jiarong Xu, Jiawei Zhang + 4 more
'Sijia Peng' 'Xuehao Zheng' 'Yun Xiong'] Effectively modeling time information and incorporating it into applications or models involving chronologically occurring events is crucial. Realworld scenarios often involve diverse and complex time patterns, which pose significant challenges for time encoding methods. While…
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan + 6 more
'Jaspreet Sahota' 'Sanjay Thakur' 'Stella Wu' 'Cathal Smyth' 'Pascal Poupart' 'Marcus A. Brubaker'] Time is an important feature in many applications involving events that occur synchronously and/or asynchronously. To effectively consume time information, recent studies have focused on designing new architectures. In…
Shanglin Zhou, Sotiris C. Masmanidis, Dean V. Buonomano
Converging evidence suggests the brain encodes time in time-varying patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Temporal tasks that require producing the same time-dependent output patterns may have distinct computational requirements in regard to the need to exhibit…
Sam Post, William Mol, Noorhan Rahmatullah, Anubhuti Goel
Whether in music, language, baking, or memory, our experience of the world is fundamentally linked to time. However, it is unclear how temporal information is encoded, particularly in the range of milliseconds to seconds. Temporal processing at this scale is critical to prediction and survival, such as in a prey…
Zoran Tiganj, Jason A. Cromer, Jefferson E. Roy, Earl K. Miller + 1 more
Cognitive theories suggest that working memory maintains not only the identity of recently-presented stimuli but also a sense of the elapsed time since the stimuli presentation. Previous studies of the neural underpinnings of working memory have focused on sustained firing, which can account for maintenance of the…
Da Xu, Chuanwei Ruan, Sushant Kumar, Evren Körpeoğlu + 1 more
Sequential modelling with self-attention has achieved cutting edge performances in natural language processing. With advantages in model flexibility, computation complexity and interpretability, self-attention is gradually becoming a key component in event sequence models. However, like most other sequence models…
Ronen Golan, Dan Zakay
While time is well acknowledged for having a fundamental part in our perception, questions on how it is represented are still matters of great debate. One of the main issues in question is whether time is represented intrinsically at the neural level, or is it represented within dedicated brain regions. We used an fMRI…
Shanglin Zhou, Sotiris C. Masmanidis, Dean V. Buonomano, Boris S. Gutkin
'Boris S. Gutkin'] Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to…
Dongyan Lin, Ann Zixiang Huang, Blake Aaron Richards
Neuroscientists have observed both cells in the brain that fire at specific points in time, known as “time cells”, and cells whose activity steadily increases or decreases over time, known as “ramping cells”. It is speculated that time and ramping cells support temporal computations in the brain and carry mnemonic…
Qun Ye, Yi Hu, Yixuan Ku, Kofi Appiah + 1 more
The human brain parsimoniously situates past events by their order in relation to time. Here, we show the posteromedial cortex geometrically abstracts the time intervals separating pairs of event-moments in long-term, episodic memory. Transcranial magnetic stimulation targeted at the precuneus erases these locally…
Gabriel M. Stine, Mehrdad Jazayeri
Cognition unfolds dynamically over flexible timescales. A major goal of the field is to understand the computational and neurobiological principles that enable this flexibility. Here, we argue that the neurobiology of timing provides a platform for tackling these questions. We begin with an overview of proposed coding…
Sidi Wu, Cédric Beaulac, Jiguo Cao
A common pipeline in functional data analysis is to first convert the discretely observed data to smooth functions, and then represent the functions by a finitedimensional vector of coefficients summarizing the information. Existing methods for data smoothing and dimensional reduction mainly focus on learning the…
Karthik H. Shankar
Encoding temporal information from the recent past as spatially distributed activations is essential in order for the entire recent past to be simultaneously accessible. Any biological or synthetic agent that relies on the past to predict/plan the future, would be endowed with such a spatially distributed temporal…
Satya Narayan Shukla, Benjamin M. Marlin
Irregular sampling occurs in many time series modeling applications where it presents a significant challenge to standard deep learning models. This work is motivated by the analysis of physiological time series data in electronic health records, which are sparse, irregularly sampled, and multivariate. In this paper…
T. Adrian Wendlandt, Patricia Wenk, Julia U. Henschke, Annika Michalek + 3 more
The ability to attend to specific moments in time is crucial for survival across species facilitating perception and motor performance by leveraging prior temporal knowledge for predictive processing. Despite its importance, the neural mechanisms underlying the utilization of macro-scale and meso-scale neural resources…
Christina Yi Jin, Anna Razafindrahaba, Raphaël Bordas, Virginie van Wassenhove
The internal clock is a psychological model for timing behavior. According to information theory, psychological time might be a manifestation of information flow during sensory processing. Herein, we tested three hypotheses: (1) whether sensory adaptation reduces (or novelty increases) the rate of the internal clock…
Dionysios Perdikis, Raoul Huys, Viktor K. Jirsa, Danielle S. Bassett
Traditional approaches to cognitive modelling generally portray cognitive events in terms of ‘discrete’ states (point attractor dynamics) rather than in terms of processes, thereby neglecting the time structure of cognition. In contrast, more recent approaches explicitly address this temporal dimension, but typically…
Michail Maniadakis, Panos Trahanias
The representation of the environment assumes the encoding of four basic dimensions in the brain, that is the 3D space and time. The vital role of time for cognition is a topic that recently attracted increasing research interest. Surprisingly, the scientific community investigating mind-time interactions has mainly…
Liisa Raud, Markus H. Sneve, Didac Vidal-Piñeiro, Øystein Sørensen + 6 more
Memory encoding and retrieval are critical sub-processes of episodic memory. While the hippocampus is involved in both, its connectivity with the neocortex during memory processing in humans has been elusive. This is partially due to variations in demands in common memory tasks, which inevitably recruit cognitive…
Lachlan Kent, Marc Wittmann
There are plenty of issues to be solved in order for researchers to agree on a neural model of consciousness. Here we emphasize an often under-represented aspect in the debate: time consciousness. Consciousness and the present moment both extend in time. Experience flows through a succession of moments and progresses…
Gabriel Rodríguez García, Gabriel Michau, Mélanie Ducoffe, Jayant Gupta + 1 more
'Jayant Gupta' 'Olga Fink'] The ability to detect anomalies in time series is considered highly valuable in numerous application domains. The sequential nature of time series objects is responsible for an additional feature complexity, ultimately requiring specialized approaches in order to solve the task. Essential…
Authors not listed
Real-world datasets in chemical engineering and bioengineering processes--such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials--can often be unlabelled or disorganized, rendering the training of existing supervised learning models ineffective at learning the…